How Predictleads CEO Roq Xever grew Predictleads to $360K revenue and 30 customers in 2018.

hello everyone my guest today is Iraq's Sivir he's from Sylvania and obviously in Europe he has a BS in electrical engineering 31 years old and on his third startup his first one failed miserably his second one became a lifestyle business now he's building his third predict leads he also loves sports and creativity and hopes to produce a movie by 2025 rocks are you ready to take us to the top I sure AM you don't seem eccentric enough to produce a movie yeah I know I guess I believe in creativity I think that drives all of us and and yeah movies are one way of I guess expressing oneself that's good alright tell us about predictor leads what's the company do and how do you make money yeah so basically we provide competitive intelligence via API we crawl billions of information pieces using machine learning and extract signals like your partnerships companies are making new clients they're signing up hiring content and then basically we provide this data we sell this data to data-driven B C's corporate VC's sales enablement platforms and strategy or innovation departments okay and is it a pure place model or they pay per lead yeah it's a pure SAS model okay and give me a general sense what's the average customer gonna pay you per month um have annual contracts that start with 6k per year okay and go up to 50k per year okay would you say 6k per years a fair average or a higher average would be around I guess 12 K okay that's so that's pretty healthy I mean this is a you're kind of you know getting into the enterprise space at a price point tell me more about the story when did you launch the company and why did you decide to get into this space yeah so we launched in 2015 why did you go in this space basically so with our previous startup we were trying to sell into the businesses to sport clubs basically and we saw that we personalized our messages the conversions went up and since we are all engineers all co-founders are engineers we try to personalize not precise we try to automate the process so that's how predict leads was born basically oh that's great okay good and so where have you scaled to today how many customers are you now working with we're yeah around 30 okay so 30 customers and have you bootstrapped the company or we raise capital um we bit strapped we received some so we were in the startup bootcamp accelerator but yeah apart from that it's bootstraps okay how much do the accelerator give you like a hundred and twenty thousand something like that you know it is a smaller one European was its yeah we gave 8 percent equity for for 15k okay but this was back when you had nothing right yeah yeah yeah okay very good and and and walk me through like the growth story how'd you get the first customer oh yeah it's doing so we're doing big data and we with big data you need a long time and lots of effort to teach the machines what is a specific signal you need lots of data it's yeah it took us a long time because I guess a year to get the first client how James Bond company between 2015 and your first client yeah so European Union has grants for more innovative companies we also our previous startup allows allows us also to work on on this one full time so yeah with the combination of both we were able to go basically a year and a half without any money basically okay and that's this your second stuff you said turn into a lifestyle business where did that I mean what is gonna give me the general size that is that do a million a year 10 million a year where is that generally no no it's it's hundreds of sound a hundred thousand per year okay smart yeah you and your founder basically run it or what yeah just the two of us okay well that's good actually if you're doing a couple hundred thousand a year and they're just two of you guys and you can use the cash flow to start the new company yeah yeah we we were looking there alright so how much do you want to sell predict leads for so you can fund your next movie eight million what do you think what do you think you have to grow revenue to to sell for 8 million yeah they say 3 times annual recurring revenue like that mmm so yeah that's 3 to 3 million oh you're doing 3 million per year if you like the business and we like the business I'm not sure if I mean it depends on lots of factors right so this number was put out yeah a bit a bit as it you'll have a business joke number but yeah it depends I think things change when you when you when you when you have a bigger revenues coming in yep and what are you doing today my monthly revenue on monthly revenues yep annual whatever whatever's easier yeah so basically um annual so till today we've we have so for 2018 we did a hundred and fifty K around there so far so far yeah yeah and we're halfway through so maybe if we double that you call it you'll do three hundred three hundred fifty grand this year yeah okay and what were you doing a year ago give me a sense of growth rate yeah so a year ago was around 4050 I guess oh well so you really grown fast yeah yeah we're actually uh it looked very dark at the end of 2017 but in the beginning of 2018 things started to kind of a match together so yeah it looks right now what does that mean what started to match together yeah basically uh so with big data you know you often you Celtic clients and getting we were when we were showing them our data the data is not great you've got many mistakes in there they're not happy and you try to correct them you work you work seven days per week you work Sundays you work holidays and then at some point yeah just the we reduce the the the errors our accuracy and match rates are really high and our clients are satisfied satisfied with our result so basically any any client that give us a try they they decide to take a next step and basically integrate with us yep yep so you mean without an intentional change you made to try and turn things around or what drove that decision the decision to to what it was not the decisions basically um which decision you mean well you said there were dark times and then it got better I'm trying to understand what did you change to make things get better so other people can learn yeah I guess we were going through the through the startup bootcamp at the time and I guess we just worked more you know we're not working from home when you're in a and we were in Amsterdam so when you are like cut off from your friends and family which is a bad thing but it on the other hands it's a it's good because you work more there or less destruction so basically we just sent more more cold emails we work more on code which is that more of everything and yeah and yeah the results got better anyway and what's the team size today how many people yeah it's a six of us six of you and are you all where you all based on in Slovenia sylvania everybody yeah yeah oh that's great so you all work in the same office or you just do coffee shops and stuff yeah yeah we we have an office often though two three of us who are founders don't go to the office every day because it's often easier less distractions if you work from home yeah but yeah what is that what churn poof it's uh I guess we didn't have lots of data for that but it's really low so basically it's uh I'm not sure my answer for the under what would you say so for the data part we have not guessed yet lost a customer we pivoted a bit first we were providing our clients with leads now we're just running the them with data so those clients that we were prodding them with leads those cab turned off a bit but with APA will be provide API access to company intelligence to business intelligence we don't have any any churn yet and and how is the data different then I assume the lead is you're sending them emails the data is you get the email address the first name last name and some other data points what other data points do you include in that yeah so basically um yeah I could compare this with like clear bit or full contact but we're different in that so we provide more advanced data we provide things like new partnerships companies are making so basically you would for example Nathan ladka dot-com I sure was there so if you would paint this with nickel not com we would return you the information on we have three main data points when are events from news basically we give you anything we find from news content from PR sites news sites if Mashable was writing about Nathan if you if you if you partnered with any companies if you made any acquisitions so this is the person we send you the signals like your partnerships the partnerships your current partnerships the clients you have signed up if you launched any products the second one is hiring content we actually check more than twelve million websites and we check their career career sites like job opening sites and extract that information so we provide if you were hiring if Nathan alcone was hiring we can provide this data two dated room PCs please see ok these are the companies who are hiring this is often a good signal that the company is growing why can't you just get that data from LinkedIn they can they can I guess LinkedIn is a bit of a gray area and you cannot get information that's easily off LinkedIn that's why also we we don't crawl LinkedIn I don't mean you crawling LinkedIn I...